Lancet Glob Health 2020;
8: e1162–85
*Collaborators listed at the end of the Article
Correspondence to:
Dr Robert C Reiner Jr, Institute for Health Metrics and Evaluation, Department of Health Metrics Science, School of Medicine, University of Washington, Seattle, WA 98121, USA bcreiner@uw.edu
Mapping geographical inequalities in access to drinking
water and sanitation facilities in low-income and
middle-income countries, 2000–17
Local Burden of Disease WaSH Collaborators*
Summary
Background
Universal access to safe drinking water and sanitation facilities is an essential human right, recognised in
the Sustainable Development Goals as crucial for preventing disease and improving human wellbeing. Comprehensive,
resolution estimates are important to inform progress towards achieving this goal. We aimed to produce
high-resolution geospatial estimates of access to drinking water and sanitation facilities.
Methods
We used a Bayesian geostatistical model and data from 600 sources across more than 88 low-income and
middle-income countries (LMICs) to estimate access to drinking water and sanitation facilities on continuous
continent-wide surfaces from 2000 to 2017, and aggregated results to policy-relevant administrative units. We estimated
mutually exclusive and collectively exhaustive subcategories of facilities for drinking water (piped water on or off
premises, other improved facilities, unimproved, and surface water) and sanitation facilities (septic or sewer sanitation,
other improved, unimproved, and open defecation) with use of ordinal regression. We also estimated the number of
diarrhoeal deaths in children younger than 5 years attributed to unsafe facilities and estimated deaths that were averted
by increased access to safe facilities in 2017, and analysed geographical inequality in access within LMICs.
Findings
Across LMICs, access to both piped water and improved water overall increased between 2000 and 2017, with
progress varying spatially. For piped water, the safest water facility type, access increased from 40·0% (95% uncertainty
interval [UI] 39·4–40·7) to 50·3% (50·0–50·5), but was lowest in sub-Saharan Africa, where access to piped water
was mostly concentrated in urban centres. Access to both sewer or septic sanitation and improved sanitation overall
also increased across all LMICs during the study period. For sewer or septic sanitation, access was 46·3% (95% UI
46·1–46·5) in 2017, compared with 28·7% (28·5–29·0) in 2000. Although some units improved access to the safest
drinking water or sanitation facilities since 2000, a large absolute number of people continued to not have access in
several units with high access to such facilities (>80%) in 2017. More than 253 000 people did not have access to sewer
or septic sanitation facilities in the city of Harare, Zimbabwe, despite 88·6% (95% UI 87·2–89·7) access overall.
Many units were able to transition from the least safe facilities in 2000 to safe facilities by 2017; for units in which
populations primarily practised open defecation in 2000, 686 (95% UI 664–711) of the 1830 (1797–1863) units
transitioned to the use of improved sanitation. Geographical disparities in access to improved water across units
decreased in 76·1% (95% UI 71·6–80·7) of countries from 2000 to 2017, and in 53·9% (50·6–59·6) of countries for
access to improved sanitation, but remained evident subnationally in most countries in 2017.
Interpretation
Our estimates, combined with geospatial trends in diarrhoeal burden, identify where efforts to increase
access to safe drinking water and sanitation facilities are most needed. By highlighting areas with successful
approaches or in need of targeted interventions, our estimates can enable precision public health to effectively
progress towards universal access to safe water and sanitation.
Funding
Bill & Melinda Gates Foundation.
Copyright
© 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
Introduction
WHO’s Integrated Global Action Plan for the Prevention
and Control of Pneumonia and Diarrhoea emphasises
the need for preventive measures.
1Unsafe water and
unsafe sanitation were the first and second leading risk
factors for under-5 mortality
from diarrhoeal diseases
globally in 2017.
2These risks increase susceptibility to the
spread of infectious agents that cause diarrhoea,
including rotavirus and Vibrio cholerae.
3–6They are also
linked to the spread of neglected tropical diseases
(NTDs),
7–10and adverse outcomes such as stunting,
wasting, and underweight.
11–13Low access to safe water
and sanitation has also been linked to broader social
outcomes such as reductions in school attendance
(particularly for girls who are menstruating), losses to
economic productivity, and undue burden on women of
time spent collecting water.
14,15Access to safe drinking water and sanitation are human
rights,
16conferring benefits to human wellbeing beyond
community has prioritised access by including safe
water and sanitation targets in both the Millennium
Development Goals and more recently in the Sustainable
Development Goals (SDGs), in which the UN called for
access to be universal (ie, 100% access) and equitable.
Despite substantial expansion of access during the
Millennium Development Goals era, it has been previously
estimated that less than 75% of the population in many
countries in sub-Saharan Africa and south and southeast
Asia had access to improved facilities in 2017.
17Previous estimates of access have been reported
primarily at the national level, as well as at the subnational
level across Africa and for a subset of other countries.
2,17–23The WHO and United Nations Children’s Fund
(WHO–UNICEF) Joint Monitoring Programme (JMP)
has analysed inequality of access by wealth quintile and
urban-rural status, as well as within subnational regions
for select locations.
24,25These analyses, however, do not
provide comprehensive estimates over space and time
across low-income and middle-income countries
(LMICs) at fine spatial scales. Understanding variation in
water and sanitation access in second
administrative-level units (eg, districts, counties; henceforth termed
units) is imperative to identifying low-access areas at
heightened risk of disease transmission,
26,27and areas
that have successfully achieved high levels of access.
Previous studies have used model-based geostatistics to
map health indicators such as under-5 mortality,
27diarrhoea incidence and prevalence,
28and child growth
failure,
29along with sociodemographic factors such as
educational attain ment,
30and interventions such as
insecticide-treated bednet coverage
31and childhood
Research in context
Evidence before this study
In light of the health risks associated with unsafe drinking
water and sanitation, as well as broader considerations of
human development, the Sustainable Development Goals
(SDGs) included the target of universal access to safe facilities
by 2030. The WHO and United Nations Children’s Fund
(WHO–UNICEF) Joint Monitoring Programme estimates access
to water and sanitation nationally and by urban and rural
areas, while the Global Burden of Diseases, Injuries, and Risk
Factors (GBD) study quantifies the health risks posed by unsafe
water and sanitation nationally and for subnational regions in
select countries. Although these and other efforts provide
valuable insights, they mask local and cross-boundary variation
and ultimately result in an incomplete picture of areas in
greatest need of intervention. The limited availability
of
accurate and wide-ranging estimates monitoring local
geographical inequalities presents a barrier to achieving
universal access to safe water and sanitation facilities. Studies
have used model-based geostatistics to map various health
and sociodemographic factors, highlighting the potential to
apply these methods for mapping access to water and
sanitation across low-income and middle-income countries
(LMICs).
Added value of this study
To our knowledge, this study presents the first high-resolution
subnational estimates of access to safe drinking water and
sanitation facilities across more than 88 LMICs and across all
indicators of access from 2000 to 2017. Our Bayesian
geostatistical models and extensive geolocated dataset account
for spatial and temporal trends, and our suite of highly resolved
spatial covariates leverage the relationships between access to
water and sanitation and other variables for improved
estimation. Additionally, this is the first application of ordinal
regression methods on water and sanitation data at large
spatial scales, allowing us to appropriately account for the
mutually exclusive and collectively exhaustive (ie, accounting
for 100% of the population) relationships between the relevant
indicators of access. We report increasing access to safe facilities
over time, but trends varied regionally, and many people
continued to have no access
to safe drinking water and
sanitation facilities in 2017 across the LMICs studied.
We estimate that 143 300 (95% uncertainty interval
126 100–163 000) deaths of children younger than 5 years were
attributable to unsafe water in sub-Saharan Africa in 2017,
yet increases in access to safe water averted more than 18 100
(15 700–21 200) child deaths in the region in that year. Averted
child deaths were concentrated in select units that had great
progress in access, while child diarrhoeal mortality increased in
other units, probably due in part to decreases in access to piped
water. Although geographical inequality decreased in most
LMICs from 2000, in some cases the lowest level of access
remained unchanged, effectively leaving behind some units,
even as progress was made nationally.
Implications of all the available evidence
Despite considerable progress since 2000, geographical
inequalities remain an obstacle to reaching the SDG target of
universal access to safely managed facilities. Our estimates
highlight where the most substantial improvements were
achieved over time, identifying areas with successful strategies
for adaptation elsewhere. Our identification of areas in which
access to safe facilities is low, combined with high-resolution
estimates of high diarrhoeal burden and child malnutrition
prevalence, calls attention to communities with high
susceptibility to the spread of infectious diseases. Although
access to safe facilities is increasing in many countries,
subnational inequalities point to the need for targeted
interventions, particularly to reach communities with the
lowest access and to increase access to the safest facility types.
Our findings can inform local level monitoring of progress
towards the SDG target, and provide a resource for decision
makers to target areas most in need of additional resources.
vaccines.
32We aimed to extend these methods to estimate
access to safe drinking water and sanitation facilities at
fine spatial resolutions.
Methods
Overview
To produce a comprehensive baseline of comparable
estimates, we leveraged the indicators used by the JMP
24and the Global Burden of Disease (GBD) study
2with a
Bayesian geostatistical model. With use of data from
600 unique datasets, we produced estimates of the relative
(proportion) and absolute (number of people) access to
water and sanitation facilities across continuous
geog-raphical surfaces and aggregated resulting predictions to
national and subnational levels (reported as second
administrative-level units) in more than 88 LMICs from
2000 to 2017. We modelled access by facility-type indicators
and for specific facilities with an ordinal modelling
framework. We report regional results according to the
GBD 2017 geographical hierarchy.
2We highlight specific
types of transitions made in access to facility types and
report the number of child diarrhoeal deaths attributed to
unsafe facilities and averted by increased access to safe
facilities. Finally, we present an analysis of variation in
subnational geographical inequality in access.
Study design
We generated estimates for two sets of four mutually
exclusive and collectively exhaustive indicators of access—
one set for drinking water and one for sanitation—with
uncertainty intervals (UIs), from 2000 to 2017. Each set of
four indicators collectively accounts for 100% of the
population in the respective geographical area. We used
an ordinal regression framework in which each indicator
was modelled using an ensemble modelling framework
for each country individually. We produced
subnational-level estimates for 88 LMICs for water and 89 LMICs for
sanitation, first estimating continent-wide surfaces at a
resolution of approximately 5 × 5 km, and then aggregating
to second and first administrative and national boundaries.
We included low, low-middle, and middle development
countries, as classified by their Socio-demographic Index
quintile,
33an indicator based on education, fertility, and
income (appendix p 94). Despite their relatively high
Socio-demographic Index, China and Libya were included
to maintain geographical continuity. Countries were
excluded if sufficient data were not available for reliable
estimation with use of our modelling paradigm. A
complete list of the countries included is available in the
appendix (p 94). This study complied with the Guidelines
for Accurate and Transparent Health Estimates Reporting
(appendix p 93).
34Further details on methods and software
used are available in the appendix (pp 9–11).
Data
Data were collated from Demographic and Health
Surveys, Multiple Indicator Cluster Surveys, and other
household surveys and censuses across 88 countries for
water and 89 for sanitation from 2000 to 2017 (inclusion
criteria details in appendix p 6). We used data from
600 unique sources—501 for water and 457 for sanitation
(some sources contained both water and sanitation data).
For water, 60·2% of our data by weighted sample size
comprised geopositioned points, and 69·3% of weighted
sanitation data were points. All other data were areal data.
Drinking water facilities were categorised as piped (piped
on or off premises), other improved (protected wells
and springs, bottled water, rainwater collection, bought
water), unimproved (unprotected wells and springs),
or surface water (figure 1). Sanitation facilities were
categorised as sewer or septic (sewer or septic tanks),
other improved (improved latrines, ventilated improved
latrines, compos ting toilets), unimproved (flush toilets to
open channels, unimproved latrines), or open defecation
(figure 1), using standardised definitions from the JMP.
17,24The resulting schema yielded mutually exclusive and
collectively exhaustive indicators for water and sanitation
access.
17Statistical analysis
To account for the ordinal data structure of the indicators
of access for water (piped, other improved, unimproved,
and surface water) and sanitation (sewer or septic,
other improved, unimproved, and open defecation), this
analysis used an ordinal continuation-ratio modelling
strategy.
35This approach allows for the simultaneous
modelling of mutually exclusive categorical responses, as
shown in similar geospatial analyses.
30,32We first modelled
the proportion of the population with access to sewer or
septic sanitation using a binomial model. We then
modelled the pr oportion of the population with access to
other improved sanitation conditioned on not having
access to sewer or septic sanitation. Subsequently, we
modelled the proportion with access to unimproved
sanitation conditioned on not having access to sewer
or septic sanitation or other improved sanitation. The
estimates from the second and third conditional models
were then combined with the estimates from the first to
generate a full set of estimates of access for all four
indicators. In this manner, the estimates and their
associated uncertainty incorporate the mutually exclusive
and collectively exhaustive data structure. The same
approach was used for the set of four indicators of access
to drinking water facilities.
For each model used in this strategy, we used an
ensemble modelling approach. Applying a stacking
ensemble modelling approach, the data were initially fit
with seven gridded-raster covariates (appendix p 28) to
three independent models using a generalised additive
model, boosted regression trees, and lasso regression. This
generalised stacking approach has been successfully used
in similar geospatial analyses of health and social data to
optimise predictive performance.
30,32Predictions were
generated from each of these child models to create raster
covariates to be used in the parent model. Subsequently,
the data were fit with the raster covariates from the child
models, with a binomial model using a spatially explicit
mixed-effects generalised linear model via integrated
nested Laplace approximation. Predictions were generated
from this model by drawing 250 samples from the
posterior distribution and taking the mean of these draws.
The 95% UIs were generated by calculating the 2·5th and
97·5th percentiles of the drawn samples. Uncertainty for
estimates are presented for piped and improved water
and sanitation indicators in the appendix (pp 39–42). To
ensure our predictions were aligned with national-level
temporal trends, we fitted a generalised additive linear
model to nationally repre sentative data for each country.
We calibrated the geospatial model to estimates from the
national model by ensuring that, when aggregated to
the national level, the geospatial estimates matched the
corresponding esti mates from the national model. Model
fits were assessed via five-fold cross-validation and
calculating out-of-sample root-mean squared errors, bias,
and 95% coverage for each model (appendix pp 10–11).
Analyses were done with R, version 3.5.0. Maps were
produced with ArcGIS Desktop 10.6. Further details for
model specification and methods can be found in the
appendix (pp 9–11).
We measured access as the proportion of the population
accessing the corresponding water and sanitation facility
type in a given geographical area at a specific time. To
assess progress over time, we calculated the mean annual
change from 2000 to 2017.
To assess the effect of changes in water and sanitation
access on diarrhoeal disease mortality in children younger
than 5 years, we used a comparative risk assess ment
framework to construct counterfactuals and assess child
deaths averted due to increased access.
2We used
estimates of diarrhoeal mortality in children younger
than 5 years available at the same spatial scales from the
geospatial analysis described by Reiner and colleagues
36for this counterfactual analysis; as such, only countries
with data available from Reiner and colleagues were
included. We combined these mortality estimates with
risk ratios estimated in GBD 2017,
2which associated
different types of water and sanitation facilities with
varied risks of diarrhoeal disease. To use the risk ratios for
different categories of water access from GBD, we
combined our estimates of water access with household
water treatment prevalence data from GBD to create
concordant categories of water facility exposures. With
these data, we calculated population attributable fractions
of child diarrhoeal deaths to unsafe water and sanitation.
2,26We then used access estimates in 2000 to calculate a
counterfactual population attributable fraction. Using
these population attributable fractions in conjunction
with the Reiner and colleagues estimates of child
diarrhoeal disease mortality across units,
36we calculated
attributable under-5
deaths for water and sanitation in
2017, as well as the number of averted child deaths in 2017
due to changes in water and sanitation access since 2000.
We propagated uncertainty by repeating the calculation
for values from each of the 250 draws of the posterior
from our model. This methodology is further outlined in
the appendix (p 11).
Additionally, we estimated inequality using subnational
variation across units and the Gini coefficient,
37which
summarises the distribution of each indicator across the
population, with a value of zero representing perfect
equality and a value of one representing maximum
inequality (appendix pp 11–12).
Role of the funding source
The funder had no role in study design, data collection,
data analysis, data interpretation, or writing of the report.
The corresponding author had full access to all the data
in the study and had final responsibility for the decision
to submit for publication.
Results
Access to all facility-type indicators for drinking water
varied spatially and temporally. Across all LMICs
assessed, access to piped water increased between
2000 and 2017 (from 40·0% [95% UI 39·4–40·7] to 50·3%
[50·0–50·5] of the population), but this trend differed
across regions (figure 2). Access to improved water overall
increased from 82·6% (95% UI
82·3–82·8) in 2000 to
87·0% (86·8–87·1) in 2017 (figure 2; appendix p 32).
Access levels for each unit are presented in the appendix
and online through our data visualisation tool.
Figure 1: Access to drinking water and sanitation indicators
The mutually exclusive and collectively exhaustive indicators modelled for water and sanitation. Each set of indicators collectively account for 100% of the population in the respective geographical area. The water indicators (piped on premises or piped off premises [piped], other improved, unimproved, and surface water) and the sanitation indicators (sewer or septic, other improved, unimproved, and open defecation) are outlined along with each indicator’s corresponding facility types. Facility types are categorised into the standardised indicators as defined by the WHO–UNICEF Joint Monitoring Programme to ensure concordance with global monitoring targets and comparability across locations.
Piped water to inside household or to yard
Facility types (water) Indicators
Piped on premises
Piped water to neighbour’s household, public stand pipe Piped off premises
Protected well, protected spring, rainwater, bottled water, tanker truck Other improved
Unprotected well, unprotected spring Unimproved
River, lake, canal, dam, surface water Surface water
Piped Improve
d
Sewer
Facility types (sanitation) Indicators
Sewer
Septic tank Septic
Improved latrines, ventilated improved latrines, compost toilets Other improved
Unimproved latrines, bucket, hanging toilet Unimproved
No facility, bush Open defecation
Sewer
or septic Improve
d
For the data visualisation tool see https://vizhub.healthdata. org/lbd/wash
Although access to piped water was lowest in
sub-Saharan Africa compared with other regions in 2017,
notable areas of high access are apparent within
sub-Saharan Africa (figure 2). Across sub-sub-Saharan Africa, at
least 80% of the population had access (henceforth
referred to as high access) to piped water in 2017 in 5·9%
(95% UI
5·7–6·2) of units, but 54·0% (53·5–54·8) of
units had decreases in piped water access from
2000 to 2017, such as the Western Urban district of Sierra
Leone (52·9% decrease [50·2–55·1]; figure 2). Units with
high access to piped water facilities in sub-Saharan Africa
mostly corresponded to large urban centres, such as
Addis Ababa, Ethiopia (97·7% [95% UI
97·0–98·1]), and
the Department of Guédiaway in Dakar, Senegal (92·9%
[91·0–94·2]). However, in urban centres and other
densely populated areas, a high absolute number of
people continued to have no access even where unit-level
access was high. For example, unit-level access to piped
water was 90·5% (95% UI 85·2–95·3) in Casablanca,
Morocco, yet 398 300 (198 500–618 500) people had no
access. Large increases in piped water access also
occurred from 2000 to 2017 for several African countries.
In Niger, national-level piped water access increased
from 23·5% (95% UI 22·7–24·4) to 47·6% (46·6–48·5),
with a 1·3% mean annual percentage-point increase. In
sub-Saharan Africa, 19·3% (95% UI 16·2–19·1) of units
increased piped water access by more than 10 percentage
points (figure 2). Access to improved water facilities
overall was widespread in Africa, despite the relatively
lower levels of piped water access: 56·8% (95% UI
56·3–57·3) of units had high access (>80%) to improved
water in 2017 (appendix p 32).
In south Asia, piped water access was relatively low,
with just 8·5% (95% UI 7·8–9·2) of units with high
access to piped water in 2017 (figure 2). However,
improved water access overall was relatively high in the
region, increasing from 83·1% (95% UI 82·9–83·3) in
2000 to 92·5% (92·3–92·6) in 2017. Access to piped water
was much higher in southeast Asia, east Asia, and
Oceania in 2017, where 58·1% (95% UI 57·5–58·5) of
units had high access. However, most of this piped water
access was concentrated in China; when excluding
China, access to piped water was just 3·2% (95% UI
2·8–3·7) in the region. Access to improved water
remained relatively stable in southeast Asia, east Asia,
and Oceania over the study period. Access was 91·2%
(95% UI 90·6–91·7) in 2000 and 88·7% (88·3–89·1) in
2017. In southeast Asia, east Asia, and Oceania overall,
access to improved water was high (>80%) in 77·0%
(95% UI
76·1–77·8) of units in 2017, and the mean
annual change in access was more than 2 percentage
points in 7·1% (6·3–7·8) of units since 2000.
Access to piped water was relatively high in much of
Latin America: 51·0% (95% UI 49·0–53·1) of units had
high access to piped water in 2017 (figure 2). Improved
water access increased in Latin America since 2000, from
89·6% (89·3–89·7) to 93·2% (93·1–93·3). Individual units
also had large increases in access to improved water—
eg, 96·4% (94·4–97·9) of units in Peru increased improved
water access by more than 10 percentage points.
We sought to identify which units made transitions
from no facility (ie, surface water or open defecation) in
2000 to improved facilities in 2017, compared with more
gradual transitions (from no facility to unimproved
facilities, or unimproved to improved facilities) over the
study period. To do so, we compared the most common
type of water and sanitation access in each unit (access
level of more than 60% of the population; figure 3).
Across all LMICs, 397 (95% UI 371–428) units in 2000 had
60% or more of their populations that relied on surface
water. Of these, 176 (156–197) units had substantial
upgrades—transitioning to 60% or more using improved
facilities by 2017. In comparison, 780 (95% UI 741–825)
units had 60% or more of people relying on surface water
or 60% or more of people using unimproved facilities in
2000; of these, relatively incremental upgrades (either
from surface water to unimproved facilities, or from
unimproved to improved water facilities) occurred in
182 (95% UI 160–205) units. The full array of model
outputs can be accessed online via our customised online
visualisation tools.
We used a comparative risk assessment framework to
estimate the number of deaths in children younger than
5 years attributed to unsafe water and sanitation in 2017
and the number of child deaths averted due to changes
in access. In 2017, 143 300 (95% UI 126 100–163 000)
deaths in children younger than 5 years in sub-Saharan
Africa were attributable to unsafe water, and 18 100
(15 700–21 200) child deaths were averted by increases in
safe water access (figure 4). In southeast Asia, east Asia,
and Oceania, 9470 (95% UI 8650–10 300) child deaths
were attributable to unsafe water in 2017, whereas
increases in safe water averted at least 1310 (1200–1440)
child deaths in 2017.
Subnational disparities in access to improved drinking
water and sanitation facilities, defined as the range of
values from the unit with the highest level of access to
the unit with the lowest level of access, are evident across
LMICs (figure 5). For improved water, disparities
decreased in 76·1% (95% UI 71·6–80·7) of LMICs from
2000 to 2017. El Salvador and Mexico had among the
greatest reductions in disparity for improved water,
although absolute and relative inequalities still persisted
in 2017; the lowest access in Mexico was 56·7% (95% UI
29·8–77·1) less than the national mean in 2000 (3·0 times
lower), and 20·8% (5·7–36·8) less than the mean
(1·3 times lower) in 2017. Disparities in access
to improved water changed in different ways across
countries. In Ethiopia, the gap between the units with
the lowest and highest access closed largely because the
lowest level of access in 2000 drew closer to the highest
level of access by 2017, increasing mean access to
improved water nationally in 2017. By comparison, mean
access to improved water was increased nationally in
For the data visualisation tool see https://vizhub.healthdata. org/lbd/wash
A
2000B
2017C
2000D
2017 Access to piped water (%) 100 50 0 Access to sewer or septic sanitation (%) 100 50 0Figure 2: Access to piped
water and sewer or septic sanitation at the second-administrative-unit level, 2000 and 2017
Access was modelled with use of model-based geostatistics for continuous continent-wide surfaces and aggregated to the second administrative level. The results for piped water are shown for years 2000 (A) and 2017 (B). The results for sewer or septic sanitation are also shown for 2000 (C) and 2017 (D). Maps reflect administrative boundaries, land cover, lakes, and population; dark grey-coloured grid cells were classified as barren or sparsely vegetated and had fewer than ten people per 1 × 1-km grid cell, or were not included in these analyses.38–43 Interactive
visualisation tools are available online. For the visualisation tools see https://vizhub.healthdata.org/ lbd/wash
Mozambique by 2017, but the lowest access level was
similar in 2000 and 2017, while the highest level of access
increased, widening the total range. Inequalities as
determined with use of the Gini coefficient revealed
additional trends. In 2000, 25 LMICs had Gini coefficients
that exceeded 0·15 for improved water access, whereas in
2017, only nine remained higher than that level.
Access to sewer or septic sanitation across all LMICs
increased from 28·7% (95% UI 28·5–29·0) in 2000 to
46·3% (46·1–46·5) in 2017, whereas access to improved
sanitation overall increased from 60·0% (59·8–60·1) to
75·8% (75·7–75·9; figure 2, appendix p 36). Some
regions saw large increases in access to sewer or septic
sanitation since 2000, whereas access remained low
across the study period in others.
Access to sewer or septic sanitation in sub-Saharan
Africa was concentrated in similar areas to piped water,
but just 1·0% (95% UI 1·0–1·0) of units had high access
in the region, such as Bulawayo, Zimbabwe (96·5%
access [95·8–97·1]; figure 2). In places with high
unit-level access, many individuals can remain without access
to sewer or septic sanitation. For instance, despite 88·6%
(87·2–89·7) of the population of Harare, Zimbabwe
having access, more than 253 000 people did not have
access in 2017.
In south Asia, there was high access to sewer or septic
sanitation in 11·3% (95% UI 9·4–12·9) of units in 2017
(figure 2). Improved sanitation overall had high
unit-level access in 69·0% (95% UI 67·6–70·4) of units in
south Asia, increasing from a regional access level of
29·4% (29·1–29·6) in 2000 to 79·4% (79·2–79·7) in 2017.
Access to sewer or septic sanitation was higher in
southeast Asia, east Asia, and Oceania compared with
south Asia in 2017; 42·0% (95% UI 40·8–43·1) of units in
the region had high access. Substantial increases in
sewer or septic sanitation access occurred over the study
period, such as in Rapti District, Mid-Western Region,
Nepal, (49·3% [95% UI 43·5–54·9] increase; mean
annual change of 2·7 percentage points). Unit-level
access to improved sanitation was high in 67·8%
(95% UI 66·8–69·0) of units in southeast Asia, east Asia,
and Oceania, increasing from 81·6% (81·2–82·0) to
85·9% (85·7–86·2) over the study period.
In Latin America, there was high access to sewer or
septic sanitation in 32·8% (95% UI 31·7–33·8) of units
in 2017 (figure 2). Latin America notably had an 11·8%
increase in access to sewer or septic sanitation over the
period (from 59·5% [59·3–59·8] to 71·3% [70·9–71·6]).
Large increases occurred in sewer or septic sanitation
from 2000, including in San Pedro Sula, Cortés,
Honduras (increase of 35·9% [32·4–39·5], mean
annual
change of 2·0 percentage points). Access to improved
sanitation overall was also high across the region, with
more than half (54·5% [53·6–55·6]) of units in Latin
America with high (>80%) access.
Of the 1830 (95% UI
1797–1863) units in which 60%
or more of people practised open defecation in 2000,
686 (664–711) transitioned substantially to having access
to improved facilities in 2017 (figure 3). By contrast,
580 (550–610) of the 5630 (5560–5690) units in which
60% or more of people practised open defecation or
in which 60% or more of people used unimproved
facilities in 2000 transitioned incrementally by 2017.
Subnation ally, many units in Ethiopia, such as Afder
Zone, Somali, increased access to improved sanitation
(11·6% [12·4–16·8] in 2000; 26·0% [22·8–29·0] in 2017)
while substantially reducing open defecation (79·7%
[77·0–82·1] in 2000; 43·3% [39·1–47·2] in 2017) over the
period. Populations with high reliance on open defecation
in 2017, were mostly concentrated in trans-border regions
in southern Angola–northern Namibia
and in west and
central Africa.
According to our comparative risk assessment
frame-work, in 2017, 182 300 (95% UI 159 900–208 200) under-5
child deaths in sub-Saharan Africa were attributed to
unsafe sanitation, whereas increases in safe sanitation
access averted at least 10 100 (8970–11 400) child deaths in
the region (figure 4). In southeast Asia, east Asia, and
Oceania, increases in safe sanitation averted at least 2750
(95% UI 2530–3040) child deaths, with 7810 (7050–8700)
child deaths attributable to unsafe sanitation in 2017,
compared with 1840 (1660–2070) averted child deaths and
4400 (4080–4690) child deaths attributable to unsafe
sanitation in Latin America in 2017.
Subnational disparities in improved sanitation
decreased in 53·9% (95% UI 50·6–59·6) of countries
from 2000, and large decreases occurred in Vietnam and
Cambodia, among other locations, although disparities
were evident across LMICs in 2017 (figure 5). The
lowest-access unit in Cambodia was 4·9 times less than the
national mean in 2000, and just 1·4 times less than in
2017. Temporal trends in disparities varied in LMICs. In
Namibia, mean access to improved sanitation increased
overall from 2000 to 2017, but the lowest level of access
remained relatively unchanged since 2000. Conversely,
the highest level of access and the lowest level of access
increased substantially in Cambodia over the study
period. With use of the Gini coefficient, we found that
many countries had consistent subnational inequality in
improved sanitation, with Gini coefficients of more than
0·15 in 37 LMICS in 2000 and 30 LMICs in 2017. Notably,
Chad, Libya, and Togo had Gini coefficients of more
than 0·35 in 2017.
Discussion
Access to safe drinking water and sanitation facilities has
improved globally between 2000, and 2017, but disparities
in access varied across LMICs, presenting a barrier to
achieving the SDG goal of universal access (100% access).
Many units, such as in Cambodia for drinking water, had
sizeable transitions, with the great majority of the
population relying on the lowest quality of facility types
in 2000 but accessing improved facilities by 2017. These
units are exemplars that merit further study to identify
Figure 3: Water and
sanitation facility types used at the second-administrative-unit level, 2000 and 2017
The co-distribution of improved, unimproved, and no facility access is shown for water for 2000 (A) and 2017 (B) and sanitation for 2000 (C), and 2017 (D). Green denotes second administrative-level units where most of the population (>60%) had access to improved facilities, blue denotes a more than 60% reliance on unimproved facilities, and red denotes more than 60% relying or surface water in A and B or practicing open defecation in C and D. Yellow indicates that there was no single dominant facility type used by more than 60% of the unit’s population. Maps reflect administrative boundaries, land cover, lakes, and population; dark grey-coloured grid cells were classified as barren or sparsely vegetated and had fewer than ten people per 1 × 1-km grid cell, or were not included in these analyses.38–43
A
2000 waterB
2017 waterC
2000 sanitationD
2017 sanitation Improved No single dominant facility type Unimproved Surface water Improved No single dominant facility type Unimproved Open defecationFigure 4: Effect of changes in
access to water and sanitation in 2017 on child diarrhoeal deaths at the second-administrative-unit level
Deaths are calculated under the counterfactual scenario in which access to safe water and sanitation remained at the values observed in the year 2000. The number of deaths attributed given access levels observed in 2017 is shown for water (A) and sanitation (C). The number of deaths averted (shown in green) or caused (shown in purple) in 2017 due to changes in access levels compared with 2000 is shown for water (B) and sanitation (D). Maps reflect administrative boundaries, land cover, lakes, and population; dark grey-coloured grid cells were classified as barren or sparsely vegetated and had fewer than ten people per 1 × 1-km grid cell, or were not included in these analyses.38–43
A
B
C
D
0 20 >200 Number of attributable deaths 0 20 >200 Number of attributable deaths >20 0 2 2 <20 Number of attributable deaths Number of averted deaths >20 0 2 2 <20 Number of attributable deaths Number of averted deathsdrivers of success for replication elsewhere. In many
countries, however, such progress was concurrent with
increasing geographical inequality, as some units were
effectively left behind. Our local-level estimates provide
information to better target interventions to ensure
progress towards greater access without increasing
geographical inequality.
Estimates of access at the unit level support local
monitoring of progress towards the SDG targets. Although
our estimates of access to safe drinking water and
sanitation facilities represent a best-case scenario of SDG
attainment, in that they do not capture all the elements of
safe management as defined by the JMP, even in the
best-case scenario it is evident that many locations will need to
scale up access to attain the goal of universal coverage.
These results also show that estimates of access stratified
by urban or
rural status only or at the first administrative
level are likely to mask further localised heterogeneity. By
providing estimates at the second administrative level, in
which programmatic decisions are often made, our results
enable local decision makers to target resources and
programmes with greater precision. Given that
household-level water, sanitation, and hygiene interventions have had
mixed results,
44–46these estimates can support targeting
interventions at the community level to maximise
efficiency and serve areas most in need of access.
Although increases in access to improved water
facilities overall were observed in sub-Saharan Africa,
access to piped water remained low in 2017. Decreases in
piped water access were particularly apparent in some
regions of sub-Saharan Africa, where demographic
changes might be outpacing infrastructure development.
The bulk of interventions in sub-Saharan Africa have
focused on increasing access to improved wells or
springs, and the relatively high rates of access to other
improved water facilities in LMICs in 2017 indicates that
0 25 50 75 100
Mongolia Tajikistan Kyrgyzstan
Tu
rkmenistan Uzbekistan
Haiti
Nicaragua Colombia Panama Bolivia Ecuador
Pe ru Hondura s Guy ana Brazil Guatemala Pa ragu ay El Salv ador DOM Me xico Afghanistan
Morocco Sudan Yemen Li
by
a
Tunisia Algeria Iraq Sy
ria
Jordan Egypt India Pakistan
Bangladesh Nepal PNG My anmar Timor−Leste Laos Indonesia China Sr i Lanka Vietnam Cambodia Philippines Thailand South Sudan
COD Madagascar Chad Guinea-Bissau Mozambique CAF Kenya Angola Sierra Leone
Zambia Togo Tanzania Niger
ia
Benin Mali Eritrea Ethiopia Senegal
Bur kina F aso Cameroon COG Niger Sw aziland Rwanda Côte d'Iv oire Zimbabw e Uganda Guinea Maur itania
Lesotho Namibia Bur
undi Gabon Malaw i Ghana Libe ria Gambia South Afr ica
Somalia Comoros Botsw
ana 0 25 50 75 100 Mongolia Tu
rkmenistan Tajikistan Kyrgyzstan Uzbekistan El Salv ador Haiti
Me
xico
Ecuador Colombia Bolivia Panama Nicaragua Hondura
s Pa ragu ay Brazil Peru Guatemala DOM Guy ana Costa Rica Li by a Sudan Yemen Morocco Afghanistan Tunisia Alge ria
Egypt Syria Iraq Jordan
Pakistan
Bangladesh
India Nepal Bhutan PNG
My
anmar
Timor−Leste
Laos
Cambodia Indonesia Vietnam
China Philippines Sr i Lanka Thailand Er itrea South Sudan Chad Ethiopia Madagascar Lesotho Mozambique
CAF Niger Benin Togo Tanzania Somalia COG Comoros Bur kina F aso Zambia Libe ria COD Sierra Leone Gabon Malaw i Angola Ke ny a Nige ria Guinea Côte d'Iv oire
Cameroon Namibia Botsw ana Mali Bur undi Guinea−Bissau Maur itania Ghana Zimbabw e Senegal South Afr ica Uganda Sw aziland Rwanda Country Access to improved water (%) Access to improved sanitation (% ) GBD super-region
Central Europe, eastern Europe, and central Asia Latin America and Caribbean North Africa and Middle East
South Asia Southeast Asia, east Asia, and Oceania Sub-Saharan Africa
Figure 5: Geographical inequality in access to improved water and sanitation
Persistence of geographical inequality in access to improved facility types for water and sanitation and changes since 2000 are shown. Each bar’s height plots the level of access to improved water and sanitation, from the lowest to the highest access second administrative-level unit in 2000 (grey) and 2017 (coloured by region). Mean access at the national level is shown as grey dots. Colours correspond to Global Burden of Disease regions. Countries not shown were excluded from the study due to limited data availability. CAF=Central African Republic. COD=Democratic Republic of Congo. COG=Republic of Congo. DOM=Dominican Republic. GNQ=Equatorial Guinea. PNG=Papua New Guinea.
these interventions have largely been successful. Further
investment in piped drinking water is needed to scale
up and maintain access and to ensure consistent and
quality access. Although initially costly, these efforts will
ultimately improve economic productivity, supporting
national development and stability.
47,48Our estimates revealed several units in which access to
the safest facility types improved substantially. Exemplars
in increasing piped water access include Svay Pao District,
Battambang, Cambodia; Jantetelco Municipality, Morelos,
Mexico; and Harari People’s National Regional State,
Ethiopia. Alongside economic growth nationally, the
autonomous Phnom Penh Water Supply Authority has
been credited with substantial expansion of Cambodia’s
urban piped water supply, whereas national and regional
policy and government investment are likely to have
played a role in Mexico and Ethiopia.
49–51Further research
on successful interventions in these locations could help
other units to adapt similar strategies. The same is true
for exemplars of increased sewer or septic sanitation,
including Kampong Chhnang District, Cambodia, and
Bagmati Zone, Central Development Region, Nepal,
where potential drivers include governance guided by
national and regional policies, infrastructure construction
and management, and (in the case of Nepal) social
movements.
52–55Urbanisation gener ally leads to increased
water and sanitation infra structure, although informal
settlements in urban areas are often excluded, presenting
a challenge to achieving equity in access.
56Although
access to the safest facility types is lowest across
sub-Saharan Africa, several units have high access in the
region. These exemplars indicate that increasing access to
piped systems in sub-Saharan Africa is entirely possible,
despite demands on infrastructure and long-term
maintenance. Here, we consider the safest facilities to be
those with the lowest health risk, defined as the lowest
associated risk-ratio for diarrhoeal disease. Considerations
of cost-effectiveness and logistical needs will probably
influence what technology is the most appropriate for any
single community, and these decisions can be more
effectively made at the local level.
In countries where access to safer facilities increased
only in units with existing access to improved facilities—
eg, transitioning from improved wells to piped—the
population relying on the worst facility types was
effectively left behind. Transitions to the safest facility
type have the greatest potential to protect health
compared with more moderate transitions.
11,57Improved
facilities might not prevent environmental contamination
and disease transmission after long-term use or in poor
environmental conditions.
58Although piped water and
sewer or septic sanitation have the greatest potential to
prevent deaths from enteric diseases,
2piped systems are
also susceptible to contamination,
59and water quality is
not currently captured in our estimates. Despite having a
smaller effect on health outcomes, transitions from
surface water or open defecation to unimproved facilities,
nonetheless represent important progress and potentially
improved quality of life, including time saved for
education and economic productivity.
14,15Decision makers
would benefit from detailed local information on the
differences in increases by type of access to better target
future interventions.
Achieving universal access in line with the SDG target
is likely to require tailored interventions framed within a
broader focus on reducing disparities. Countries such as
Mozambique were able to increase mean access to
improved water facilities, but although the highest level
of access increased, the lowest level was relatively stable
from 2000 to 2017, potentially reflecting improvements
concentrated in urban centres with large populations
where access was already higher. Targeted rural
inter-ventions might be needed to serve those with the lowest
levels of access, for whom increases in access have not
been as substantial. Ethiopia, for example, was able to
increase the lowest levels of access to improved water
facilities by 2017. In remote com munities where a small
number of people continue to have no access
despite a
high national access level, local-level investments in
infrastructure are probably most suitable to address this
disparity. Conversely, in Nigeria, where large numbers of
people concentrated in single units do not have
access
to safe sanitation, more centralised solutions might
best serve these dense urban populations. Examples such
as improved water access in Cambodia, which saw
pronounced increases in both the lowest access and
highest access relative to 2000 levels, potentially present
models for adoption elsewhere. Previous studies have
identified poor, indigenous, and rural communities as
the least likely to have access.
51,60Although the disparity
in access between urban and rural areas has long been
recognised, our estimates underscore the ongoing need
for investment in rural water and sanitation.
Our results identified several units in which changes in
access to safe water averted relatively few child deaths, or
decreased access to safe water led to increased child
diarrhoeal mortality. This finding largely reflects decreases
in piped water access in some units—potentially driven in
part by conflict and instability,
61particularly in areas such
as in northeastern Nigeria—and suggests that what
improvements in access did occur were not for the safest
forms of facilities or that the improvements were not of a
sufficient magnitude to have a major effect. In addition,
our estimates do not capture other elements of safety,
such as safe water storage and safe disposal of child faeces,
which could drive reductions in diarrhoeal deaths.
4Although the absolute number of deaths averted in a unit
might not be large, the number of deaths attributable to
unsafe water and sanitation in 2017 remains high,
indicating that efforts to expand access would also reduce
child mortality. Investments in increasing access to
improved water and sanitation facilities are likely to have
the greatest effect on reducing child deaths due to
diarrhoea when coupled with other measures that protect
children.
1,26Other factors, such as treatment with oral
rehydration solution, could have a combined effect with
water and sanitation access on preventing child diarrhoeal
deaths. Coverage of oral rehydration therapy over the
study period has been mapped in a companion article by
Wiens and colleagues.
62More broadly, strengthening
primary health-care systems and addressing social and
economic determinants of health will also be imperative
to successfully reduce disease and prevent child deaths.
Our estimates can help by identifying areas susceptible to
disease spread, aiding vaccine-targeting efforts, and
assisting disease elimination campaigns in focusing on
where they will be most successful. The relationship
between access to water and sanitation and the spread of
NTDs provides a particular opportunity to coordinate and
improve disease prevention efforts across sectors.
10,63,64Water, sanitation, and hygiene are also integral to the
treatment of some NTDs, such as lymphatic filariasis and
podoconiosis.
65,66Our estimates facilitate targeting
infrastructure investments toward communities with a
high burden of NTDs, such as those identified through
the Global Trachoma Mapping Project,
67and low levels of
access to drinking water and sanitation facilities.
The geostatistical nature of this analysis allows for
explicit incorporation of geopositioned data, more
effectively capturing local variation in access over space
and time, compared with studies that use exclusively
areal data.
13Additionally, the use of a continuation-ratio
modelling framework appropriately accounts for the
ordinal relationships between indicators of water or
sanitation facility type. This study also uses an extensive
suite of covariates to leverage the complex relationships
between water and sanitation access and environmental,
social, and public health correlates at the local level. Our
findings highlight the need to increase investment,
assess existing interventions, scale up and expand
successes, and improve monitoring of access to these
facilities. Ultimately, these estimates, in combination
with parallel work on oral rehydration therapy,
62provide
an actionable atlas to progress toward universal access,
reduce child diarrhoeal mortality and the spread of
disease, and improve wellbeing worldwide.
The data and methodology underlying these results
have several limitations. First, SDG 1.4.1 aims to achieve
universal access to basic services, and SDG 6 aims to
achieve universal access to safely managed services;
however, current data are insufficient to produce reliable
estimates of these dimensions of access at the spatial and
temporal scale presented here. Consequently, this
analysis focused on access by facility type classification
(figure 1), and our estimates provide a best-case scenario
for the SDGs (all improved facilities are safely managed
and provide basic services). Second, despite the fine
spatial resolution of this study, these results might not
fully represent intra-urban disparities in water and
sanitation. Third, to incorporate the vast quantity of areal
data in a geostatistical framework, areal data were
transformed into geopositioned point data over the
corresponding geographical area. This method could
result in smoothed estimates in areas with predominantly
areal data. Fourth, our data do not capture the impacts of
conflicts or climate change-related weather events and
disasters, and data for locations affected by these factors
might not reflect current conditions. Fifth, survey data
are subject to known biases and inaccuracies in reporting,
and these issues coupled with data scarcity in some
locations could affect the accuracy of our estimates.
Sixth, our analysis of inequality is limited to variation in
access and does not encompass social and economic
factors affecting inequality in access. Seventh, uncertainty
in existing population estimates affects the precision of
our count estimates of access. Finally, although our
model generates estimates of uncertainty considering
the covariates as well as spatiotemporal trends,
un-certainty is not explicitly incorporated from the survey
design or the intermediate covariates generated from our
stacking procedure (appendix p 9) due to computational
limitations.
We plan to adopt the newly updated global indicators of
water and sanitation access, including categories of basic
and safely managed, by the WHO–UNICEF JMP.
Although our study identified the best performing units
and diverse modes of improvement across facilities, it
was beyond our scope to identify the specific factors and
interventions that contributed to these successes. Further
research on potential shared characteristics across
countries and units achieving high and equitable access
could inform potential avenues for policy makers to
adopt, particularly in light of the shifting focus from
improved facility access to safely managed services. This
analysis provides a comprehensive set of estimates across
all facility types and locations; additional research with
these methods to explore aspects presented here in
greater detail would further enable prioritisation and
targeting of water and sanitation interventions at the
local level.
Despite substantial gains in some regions, accelerated
progress will be necessary to achieve universal and
equitable access to the safest forms of drinking water and
sanitation facilities in line with SDG targets. Sub-Saharan
Africa, in particular, would probably benefit from a
precision public health approach to increasing access.
This analysis improves on traditional national and
subnational estimates, providing an analysis of both
absolute and relative progress and identifies communities
with low access as well as exemplars of improved access
at the second administrative level. Our results indicate
that vast geographical inequalities persist in both the
proportion and number of people with access within
countries, as well as in improvements of the quality of
facilities over time. Local estimates can guide targeting of
disease prevention efforts, particularly vaccines and
interventions for nutrition and NTDs, to the communities
with the lowest access. Ultimately, our estimates provide
a resource for researchers, policy makers, and
implementers to improve drinking water and sanitation
access at local to national geographical scales, ensuring
that all have access to this basic human right.
Local Burden of Disease WaSH Collaborators
Aniruddha Deshpande, Molly K Miller-Petrie, Paulina A Lindstedt, Mathew M Baumann, Kimberly B Johnson, Brigette F Blacker, Hedayat Abbastabar, Foad Abd-Allah, Ahmed Abdelalim,
Ibrahim Abdollahpour, Kedir Hussein Abegaz, Ayenew Negesse Abejie, Lucas Guimarães Abreu, Michael R M Abrigo, Ahmed Abualhasan, Manfred Mario Kokou Accrombessi, Abdu A Adamu,
Oladimeji M Adebayo, Isaac Akinkunmi Adedeji,
Rufus Adesoji Adedoyin, Victor Adekanmbi, Olatunji O Adetokunboh, Tara Ballav Adhikari, Mohsen Afarideh, Marcela Agudelo-Botero, Mehdi Ahmadi, Keivan Ahmadi, Anwar E Ahmed,
Muktar Beshir Ahmed, Temesgen Yihunie Akalu, Ali S Akanda, Fares Alahdab, Ziyad Al-Aly, Noore Alam, Samiah Alam, Genet Melak Alamene, Turki M Alanzi, James Albright,
Ammar Albujeer, Jacqueline Elizabeth Alcalde-Rabanal, Animut Alebel, Zewdie Aderaw Alemu, Muhammad Ali, Mehran Alijanzadeh, Vahid Alipour, Syed Mohamed Aljunid, Ali Almasi,
Amir Almasi-Hashiani, Hesham M Al-Mekhlafi, Khalid A Altirkawi, Nelson Alvis-Guzman, Nelson J Alvis-Zakzuk, Saeed Amini, Arianna Maever L Amit, Gianna Gayle Herrera Amul, Catalina Liliana Andrei, Mina Anjomshoa, Ansariadi Ansariadi, Carl Abelardo T Antonio, Benny Antony, Ernoiz Antriyandarti, Jalal Arabloo, Hany Mohamed Amin Aref, Olatunde Aremu, Bahram Armoon, Amit Arora, Krishna K Aryal, Afsaneh Arzani, Mehran Asadi-Aliabadi, Daniel Asmelash, Hagos Tasew Atalay, Seyyed Shamsadin Athari, Seyyede Masoume Athari, Sachin R Atre, Marcel Ausloos, Shally Awasthi, Nefsu Awoke,
Beatriz Paulina Ayala Quintanilla, Getinet Ayano,
Martin Amogre Ayanore, Yared Asmare Aynalem, Samad Azari, Andrew S Azman, Ebrahim Babaee, Alaa Badawi, Mojtaba Bagherzadeh, Shankar M Bakkannavar, Senthilkumar Balakrishnan, Maciej Banach, Joseph Adel Mattar Banoub, Aleksandra Barac, Miguel A Barboza, Till Winfried Bärnighausen, Sanjay Basu, Vo Dinh Bay, Mohsen Bayati, Neeraj Bedi, Mahya Beheshti, Meysam Behzadifar, Masoud Behzadifar, Diana Fernanda Bejarano Ramirez, Michelle L Bell, Derrick A Bennett, Habib Benzian, Dessalegn Ajema Berbada, Robert S Bernstein, Anusha Ganapati Bhat, Krittika Bhattacharyya, Soumyadeep Bhaumik, Zulfiqar A Bhutta, Ali Bijani, Boris Bikbov,
Muhammad Shahdaat Bin Sayeed, Raaj Kishore Biswas, Somayeh Bohlouli, Soufiane Boufous, Oliver J Brady,
Andrey Nikolaevich Briko, Nikolay Ivanovich Briko, Gabrielle B Britton, Alexandria Brown, Sharath Burugina Nagaraja, Zahid A Butt, Luis Alberto Cámera, Ismael R Campos-Nonato,
Julio Cesar Campuzano Rincon, Jorge Cano, Josip Car, Rosario Cárdenas, Felix Carvalho, Carlos A Castañeda-Orjuela, Franz Castro, Ester Cerin, Binaya Chalise, Vijay Kumar Chattu, Ken Lee Chin,
Devasahayam J Christopher, Dinh-Toi Chu, Natalie Maria Cormier, Vera Marisa Costa, Elizabeth A Cromwell, Abel Fekadu Dadi, Tukur Dahiru, Saad M A Dahlawi, Rakhi Dandona, Lalit Dandona, Anh Kim Dang, Farah Daoud, Aso Mohammad Darwesh,
Amira Hamed Darwish, Ahmad Daryani, Jai K Das, Rajat Das Gupta, Aditya Prasad Dash, Claudio Alberto Dávila-Cervantes,
Nicole Davis Weaver, Fernando Pio De la Hoz, Jan-Walter De Neve, Dereje Bayissa Demissie, Gebre Teklemariam Demoz,
Edgar Denova-Gutiérrez, Kebede Deribe, Assefa Desalew,
Samath Dhamminda Dharmaratne, Preeti Dhillon, Meghnath Dhimal, Govinda Prasad Dhungana, Daniel Diaz, Isaac Oluwafemi Dipeolu, Hoa Thi Do, Christiane Dolecek, Kerrie E Doyle, Eleonora Dubljanin, Andre Rodrigues Duraes, Hisham Atan Edinur, Andem Effiong, Aziz Eftekhari, Nevine El Nahas, Maysaa El Sayed Zaki, Maha El Tantawi, Hala Rashad Elhabashy, Shaimaa I El-Jaafary, Ziad El-Khatib, Hajer Elkout, Aisha Elsharkawy, Shymaa Enany, Daniel Adane Endalew, Babak Eshrati, Sharareh Eskandarieh, Arash Etemadi, Oluchi Ezekannagha, Emerito Jose A Faraon, Mohammad Fareed, Andre Faro, Farshad Farzadfar, Alebachew Fasil, Mehdi Fazlzadeh, Valery L Feigin, Wubalem Fekadu, Netsanet Fentahun,
Seyed-Mohammad Fereshtehnejad, Eduarda Fernandes, Irina Filip, Florian Fischer, Carsten Flohr, Nataliya A Foigt,
Morenike Oluwatoyin Folayan, Masoud Foroutan,
Richard Charles Franklin, Joseph Jon Frostad, Takeshi Fukumoto, Mohamed M Gad, Gregory M Garcia, Augustine Mwangi Gatotoh, Reta Tsegaye Gayesa, Ketema Bizuwork Gebremedhin,
Yilma Chisha Dea Geramo, Hailay Abrha Gesesew,
Kebede Embaye Gezae, Ahmad Ghashghaee, Farzaneh Ghazi Sherbaf, Tiffany K Gill, Paramjit Singh Gill, Themba G Ginindza, Alem Girmay, Zemichael Gizaw, Amador Goodridge, Sameer Vali Gopalani, Alessandra C Goulart, Bárbara Niegia Garcia Goulart, Ayman Grada, Manfred S Green, Mohammed Ibrahim Mohialdeen Gubari, Harish Chander Gugnani, Davide Guido, Rafael Alves Guimarães, Yuming Guo, Rahul Gupta, Rajeev Gupta, Giang Hai Ha, Juanita A Haagsma, Nima Hafezi-Nejad, Dessalegn H Haile, Michael Tamene Haile, Brian J Hall, Samer Hamidi, Demelash Woldeyohannes Handiso, Hamidreza Haririan, Ninuk Hariyani, Ahmed I Hasaballah, Md Mehedi Hasan, Amir Hasanzadeh, Hamid Yimam Hassen, Desta Haftu Hayelom, Mohamed I Hegazy, Behzad Heibati, Behnam Heidari, Delia Hendrie, Andualem Henok, Claudiu Herteliu, Fatemeh Heydarpour, Hagos Degefa de Hidru, Thomas R Hird, Chi Linh Hoang, Gillian I Hollerich, Praveen Hoogar, Naznin Hossain,
Mehdi Hosseinzadeh, Mowafa Househ, Guoqing Hu, Ayesha Humayun, Syed Ather Hussain, Mamusha Aman A Hussen,
Segun Emmanuel Ibitoye, Olayinka Stephen Ilesanmi, Milena D Ilic, Mohammad Hasan Imani-Nasab, Usman Iqbal,
Seyed Sina Naghibi Irvani, Sheikh Mohammed Shariful Islam, Rebecca Q Ivers, Chinwe Juliana Iwu, Nader Jahanmehr, Mihajlo Jakovljevic, Amir Jalali, Achala Upendra Jayatilleke, Ensiyeh Jenabi, Ravi Prakash Jha, Vivekanand Jha, John S Ji,
Jost B Jonas, Jacek Jerzy Jozwiak, Ali Kabir, Zubair Kabir, Tanuj Kanchan, André Karch, Surendra Karki, Amir Kasaeian,
Gebremicheal Gebreslassie Kasahun, Habtamu Kebebe Kasaye, Getachew Mullu Kassa, Gebrehiwot G Kassa, Gbenga A Kayode, Mihiretu M Kebede, Peter Njenga Keiyoro, Daniel Bekele Ketema, Yousef Saleh Khader, Morteza Abdullatif Khafaie, Nauman Khalid, Rovshan Khalilov, Ejaz Ahmad Khan, Junaid Khan,
Md Nuruzzaman Nuruzzaman Khan, Khaled Khatab, Mona M Khater, Amir M Khater, Maryam Khayamzadeh, Mohammad Khazaei, Mohammad Hossein Khosravi, Jagdish Khubchandani, Ali Kiadaliri, Yun Jin Kim, Ruth W Kimokoti, Sezer Kisa, Adnan Kisa, Sonali Kochhar, Tufa Kolola, Hamidreza Komaki, Soewarta Kosen, Parvaiz A Koul, Ai Koyanagi, Kewal Krishan, Barthelemy Kuate Defo, Nuworza Kugbey, Pushpendra Kumar, G Anil Kumar, Manasi Kumar, Dian Kusuma, Carlo La Vecchia, Ben Lacey, Aparna Lal, Dharmesh Kumar Lal, Hilton Lam, Faris Hasan Lami, Van Charles Lansingh, Savita Lasrado, Georgy Lebedev, Paul H Lee, Kate E LeGrand, Mostafa Leili, Tsegaye Lolaso Lenjebo, Cheru Tesema Leshargie, Aubrey J Levine, Sonia Lewycka, Shanshan Li, Shai Linn, Shiwei Liu,
Jaifred Christian F Lopez, Platon D Lopukhov,
Muhammed Magdy Abd El Razek, D R Mahadeshwara Prasad, Phetole Walter Mahasha, Narayan B Mahotra, Azeem Majeed, Reza Malekzadeh, Deborah Carvalho Malta, Abdullah A Mamun, Navid Manafi, Mohammad Ali Mansournia,
Chabila Christopher Mapoma, Gabriel Martinez, Santi Martini, Francisco Rogerlândio Martins-Melo, Manu Raj Mathur, Benjamin K Mayala, Mohsen Mazidi, Colm McAlinden, Birhanu Geta Meharie, Man Mohan Mehndiratta, Entezar Mehrabi Nasab, Kala M Mehta, Teferi Mekonnen, Tefera Chane Mekonnen, Gebrekiros Gebremichael Meles, Hagazi Gebre Meles, Peter T N Memiah, Ziad A Memish, Walter Mendoza, Ritesh G Menezes, Seid Tiku Mereta,
Tuomo J Meretoja, Tomislav Mestrovic, Workua Mekonnen Metekiya, Bartosz Miazgowski, Ted R Miller, GK Mini, Erkin M Mirrakhimov, Babak Moazen, Bahram Mohajer, Yousef Mohammad,
Dara K Mohammad, Naser Mohammad Gholi Mezerji, Roghayeh Mohammadibakhsh, Shafiu Mohammed,
Jemal Abdu Mohammed, Hassen Mohammed, Farnam Mohebi, Ali H Mokdad, Yoshan Moodley, Ghobad Moradi, Masoud Moradi, Mohammad Moradi-Joo, Paula Moraga, Linda Morales, Abbas Mosapour,
